How-toOfficial
多智能体系统上生产的 5 个难题：Deep Insight 的解法
5 production challenges in multi-agent systems and how Deep Insight solved them
Why we picked it
AWS 拆解了多智能体系统从原型到上线的 5 个坑，用开源项目 Deep Insight 逐个给出解法，做 Agent 工程的直接抄作业。
很多团队几天内就能搭出多智能体原型，但一到生产环境就卡壳。这篇文章梳理了 5 类生产难题：编排、按 Agent 选模型、可靠运行、安全代码执行和监控。作者以开源多智能体系统 Deep Insight 为例，逐一说明它在 AWS 上如何解决每个问题。
Original · AWS Machine Learning Blog
5 production challenges in multi-agent systems and how Deep Insight solved them
Many teams build a multi-agent AI prototype in days but hit a wall in production. This post defines five production challenges (orchestration, per-agent model selection, reliable operation, secure code execution, and monitoring) and shows how Deep Insight, an open source multi-agent system on AWS, solves each.
